{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:7OGH43QS2EPIY7NAE3IZ5B6CX5","short_pith_number":"pith:7OGH43QS","canonical_record":{"source":{"id":"2110.07439","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-14T15:06:30Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ee227687b063d161f6921b9d8b2a6a1cdd441b8f85d9d4b51351be2ee79bbeb2","abstract_canon_sha256":"76ee6ed242e3060e78c597e9eb081c03ad59eecb3818442a3932b7acb65ad808"},"schema_version":"1.0"},"canonical_sha256":"fb8c7e6e12d11e8c7da026d19e87c2bf60b83c246a3a99d54db2949324551521","source":{"kind":"arxiv","id":"2110.07439","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.07439","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"arxiv_version","alias_value":"2110.07439v2","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.07439","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"pith_short_12","alias_value":"7OGH43QS2EPI","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"pith_short_16","alias_value":"7OGH43QS2EPIY7NA","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"pith_short_8","alias_value":"7OGH43QS","created_at":"2026-07-05T03:26:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:7OGH43QS2EPIY7NAE3IZ5B6CX5","target":"record","payload":{"canonical_record":{"source":{"id":"2110.07439","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-14T15:06:30Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ee227687b063d161f6921b9d8b2a6a1cdd441b8f85d9d4b51351be2ee79bbeb2","abstract_canon_sha256":"76ee6ed242e3060e78c597e9eb081c03ad59eecb3818442a3932b7acb65ad808"},"schema_version":"1.0"},"canonical_sha256":"fb8c7e6e12d11e8c7da026d19e87c2bf60b83c246a3a99d54db2949324551521","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:26:21.070964Z","signature_b64":"XBgnphnQZJHelApaBmkWfmoLKvm0674YUoGMVfaUWbNFl/683/4qP5UYKwdJFX6z39PKTh5fmG1+/yjpl2R/Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fb8c7e6e12d11e8c7da026d19e87c2bf60b83c246a3a99d54db2949324551521","last_reissued_at":"2026-07-05T03:26:21.070532Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:26:21.070532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.07439","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:26:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6yN1awmA+uNm90To59Zyp9slXSwF44aWRk/oKnsdV/vGOUKrshq/kwRFtWTKFykk5/nPqyFQcNiUFYyJ6EIxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T05:06:06.885571Z"},"content_sha256":"54da9630477b4477a75e2f402720837f6d7449dadb86beeb49b3ac47d8726d17","schema_version":"1.0","event_id":"sha256:54da9630477b4477a75e2f402720837f6d7449dadb86beeb49b3ac47d8726d17"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:7OGH43QS2EPIY7NAE3IZ5B6CX5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Inverse Problems Leveraging Pre-trained Contrastive Representations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Alexandros G. Dimakis, Georgios Smyrnis, Matt Jordan, Sriram Ravula","submitted_at":"2021-10-14T15:06:30Z","abstract_excerpt":"We study a new family of inverse problems for recovering representations of corrupted data. We assume access to a pre-trained representation learning network R(x) that operates on clean images, like CLIP. The problem is to recover the representation of an image R(x), if we are only given a corrupted version A(x), for some known forward operator A. We propose a supervised inversion method that uses a contrastive objective to obtain excellent representations for highly corrupted images. Using a linear probe on our robust representations, we achieve a higher accuracy than end-to-end supervised ba"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.07439","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2110.07439/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:26:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BGWDPIFTUTr+0bRfS8uvzImzOHp76DtaAdQMntbApQ1Cn/XsPB16yTj3bf9u9o40Seo9pL4QFeQypDtY7nZMCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T05:06:06.886626Z"},"content_sha256":"034cc4b48ddee50c9a32af697997950f9147add72b3a113ea83724b5ad4dfc45","schema_version":"1.0","event_id":"sha256:034cc4b48ddee50c9a32af697997950f9147add72b3a113ea83724b5ad4dfc45"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7OGH43QS2EPIY7NAE3IZ5B6CX5/bundle.json","state_url":"https://pith.science/pith/7OGH43QS2EPIY7NAE3IZ5B6CX5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7OGH43QS2EPIY7NAE3IZ5B6CX5/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-16T05:06:06Z","links":{"resolver":"https://pith.science/pith/7OGH43QS2EPIY7NAE3IZ5B6CX5","bundle":"https://pith.science/pith/7OGH43QS2EPIY7NAE3IZ5B6CX5/bundle.json","state":"https://pith.science/pith/7OGH43QS2EPIY7NAE3IZ5B6CX5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7OGH43QS2EPIY7NAE3IZ5B6CX5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:7OGH43QS2EPIY7NAE3IZ5B6CX5","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"76ee6ed242e3060e78c597e9eb081c03ad59eecb3818442a3932b7acb65ad808","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-14T15:06:30Z","title_canon_sha256":"ee227687b063d161f6921b9d8b2a6a1cdd441b8f85d9d4b51351be2ee79bbeb2"},"schema_version":"1.0","source":{"id":"2110.07439","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.07439","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"arxiv_version","alias_value":"2110.07439v2","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.07439","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"pith_short_12","alias_value":"7OGH43QS2EPI","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"pith_short_16","alias_value":"7OGH43QS2EPIY7NA","created_at":"2026-07-05T03:26:21Z"},{"alias_kind":"pith_short_8","alias_value":"7OGH43QS","created_at":"2026-07-05T03:26:21Z"}],"graph_snapshots":[{"event_id":"sha256:034cc4b48ddee50c9a32af697997950f9147add72b3a113ea83724b5ad4dfc45","target":"graph","created_at":"2026-07-05T03:26:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2110.07439/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study a new family of inverse problems for recovering representations of corrupted data. We assume access to a pre-trained representation learning network R(x) that operates on clean images, like CLIP. The problem is to recover the representation of an image R(x), if we are only given a corrupted version A(x), for some known forward operator A. We propose a supervised inversion method that uses a contrastive objective to obtain excellent representations for highly corrupted images. Using a linear probe on our robust representations, we achieve a higher accuracy than end-to-end supervised ba","authors_text":"Alexandros G. Dimakis, Georgios Smyrnis, Matt Jordan, Sriram Ravula","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-14T15:06:30Z","title":"Inverse Problems Leveraging Pre-trained Contrastive Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.07439","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:54da9630477b4477a75e2f402720837f6d7449dadb86beeb49b3ac47d8726d17","target":"record","created_at":"2026-07-05T03:26:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"76ee6ed242e3060e78c597e9eb081c03ad59eecb3818442a3932b7acb65ad808","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-14T15:06:30Z","title_canon_sha256":"ee227687b063d161f6921b9d8b2a6a1cdd441b8f85d9d4b51351be2ee79bbeb2"},"schema_version":"1.0","source":{"id":"2110.07439","kind":"arxiv","version":2}},"canonical_sha256":"fb8c7e6e12d11e8c7da026d19e87c2bf60b83c246a3a99d54db2949324551521","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb8c7e6e12d11e8c7da026d19e87c2bf60b83c246a3a99d54db2949324551521","first_computed_at":"2026-07-05T03:26:21.070532Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:26:21.070532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XBgnphnQZJHelApaBmkWfmoLKvm0674YUoGMVfaUWbNFl/683/4qP5UYKwdJFX6z39PKTh5fmG1+/yjpl2R/Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:26:21.070964Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.07439","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:54da9630477b4477a75e2f402720837f6d7449dadb86beeb49b3ac47d8726d17","sha256:034cc4b48ddee50c9a32af697997950f9147add72b3a113ea83724b5ad4dfc45"],"state_sha256":"2b60a6efcba29eb8b8f3ae7b179d66d3a61f962deeb7dceb9cf3ddabe1eb05dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2BiOE7y8GJqiyxIRExDU4/MRjPV+7uFB7EC+kLlNjrehLftL/Icd9oGPeFR6KLzzgtB+3gvmnSC+rhSlNHcJBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T05:06:06.892783Z","bundle_sha256":"bdac87b2e4222ceaa43200ab295d863a0d17b511c1f8c6d9ba4fbfec267c7cd1"}}